Robust Two-View External Calibration by Combining Lines and Scale Invariant Point Features

Authors:
Xiaolong Zhang;Jin Zhou;Baoxin Li
Affiliations:
Department of Computer Science and Engineering, Arizona State University, Tempe, USA;Department of Computer Science and Engineering, Arizona State University, Tempe, USA;Department of Computer Science and Engineering, Arizona State University, Tempe, USA
Venue:
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Year:
2008

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Abstract

In this paper we present a new approach for automatic external calibration for two camera views under general motion based on both line and point features. Detected lines are classified into two classes: either vertical or horizontal. We make use of these lines extensively to determine the camera pose. First, the rotation is estimated directly from line features using a novel algorithm. Then normalized point features are used to compute the translation based on epipolar constraint. Compared with point-feature-based approaches, the proposed method can handle well images with little texture. Also, our method bypasses sophisticated post-processing stage that is typically employed by other line-feature-based approaches. Experiments show that, although our approach is simple to implement, the performance is reliable in practice.